Are Clinical BERT Models Privacy Preserving? The Difficulty of Extracting Patient-Condition Associations. - Thomas Vakili; Hercules Dalianis (HUMAN@AAAI Fall Symposium, 2021)

Utility Preservation of Clinical Text After De-Identification. - Thomas Vakili; Hercules Dalianis (BioNLP@ACL, 2022)

Downstream Task Performance of BERT Models Pre-Trained Using Automatically De-Identified Clinical Data. - Thomas Vakili; Anastasios Lamproudis; Aron Henriksson; Hercules Dalianis (LREC, 2022)

Using Membership Inference Attacks to Evaluate Privacy-Preserving Language Modeling Fails for Pseudonymizing Data. - Thomas Vakili; Hercules Dalianis (NoDaLiDa, 2023)

A Privacy-Preserving Corpus for Occupational Health in Spanish: Evaluation for NER and Classification Tasks. - Claudio Aracena; Luis Miranda; Thomas Vakili; Fabián Villena; Tamara Quiroga; Fredy Núñez-Torres; Victor Rocco; Jocelyn Dunstan (ClinicalNLP@NAACL, 2024)

A pseudonymized corpus of occupational health narratives for clinical entity recognition in Spanish. - Jocelyn Dunstan; Thomas Vakili; Luis Miranda; Fabián Villena; Claudio Aracena; Tamara Quiroga; Paulina Vera; Sebastián Viteri Valenzuela; Victor Rocco (BMC Medical Informatics Decis. Mak., 2024)

Data-Constrained Synthesis of Training Data for De-Identification. - Thomas Vakili; Aron Henriksson; Hercules Dalianis (ACL (1), 2025)